This paper proposes a method for auditing parliamentary elections to certify a winning majority instead of individual seats, reducing the number of ballots inspected by almost a thousand-fold.

The paper introduces two novel risk-limiting audit techniques—statistical manifest generation and direct ballot selection—that significantly reduce the computational complexity and time required for p…

This paper improves an algorithm for computing lower bounds on the margin of a Single Transferable Vote (STV) election, making risk-limiting audits more practical.

The paper introduces ACE, a novel voting protocol that achieves end-to-end verifiability and strong voter privacy by combining tally-hiding aggregation with an Audit-or-Cast challenge, eliminating the…

This paper proposes a comprehensive, risk-based auditing framework designed to help internal and external auditors assess the cybersecurity risks posed by diverse IoT devices within corporate and indu…

This paper proposes a secure liquid democracy mechanism using sealed delegation and ranked multi-delegation with personal fallback ballots, and evaluates its impact on representational accuracy and vo…

The paper introduces and demonstrates 'narrow secret loyalties,' a novel type of covert model manipulation that biases model output toward a specific principal's interests under narrow conditions, whi…

The paper demonstrates that current safety audit metrics are susceptible to strategic platform manipulation, proposing a more robust 'semantic-envelope' metric that better certifies genuine harm reduc…

This paper characterizes the label complexity of certifying small missed mass in an empirical pipeline and shows that auditing the excluded pool is minimax rate-optimal.

The paper proposes a non-cryptographic, End-to-End Verifiable (E2E-V) voting scheme that achieves Software-Free Verification (SFV) by allowing voters to audit election integrity using only basic arith…

The paper proposes a tamper-proof fraud detection system that uses blockchain smart contracts to immutably record ML predictions and workflow executions, addressing the vulnerability of controllable a…

This paper analyzes the Loki e-voting protocol, demonstrating that while it attempts to solve coercion-resistance without pre-agreed secrets, it remains vulnerable to specific attacks, suggesting that…

This paper develops a data-poisoning audit for augmented inverse-probability-weighted estimation to prevent strategic record selection in observational causal analyses.

This paper analyzes differential privacy auditing as a bilevel game, showing that naive audit designs fail to detect true harm when developers strategically respond, and proposes an optimal, single-le…

The paper conducts an interpretability-driven safety audit of eight state-of-the-art LLMs, demonstrating that while interpretability-based steering is a powerful auditing tool, model robustness varies…

The paper proposes FinSec, a novel four-tier security detection framework, to robustly identify complex financial risks and suspicious dialogue patterns in LLM-powered financial agents, achieving stat…

The paper demonstrates that the Brazilian e-Voting Machine interface generates a simple and highly distinctive electromagnetic spectral signature, raising significant concerns about its susceptibility…

The paper introduces an efficient, lightweight LLM framework for smart contract auditing that decouples the audit process into multiple components, achieving high accuracy while significantly reducing…

This paper analyzes how a financial-technology organization operationalizes the ISO/IEC 27001:2022 standard by examining eight core security procedures, concluding that an effective ISMS requires a ti…

The paper introduces an optimal black-box auditing framework using Donsker-Varadhan estimators to estimate Rényi differential privacy (RDP) guarantees for machine learning algorithms.